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Well, not if you’re a magazine publisher or a Pink Floyd fan. But otherwise, it’s a truism that guides many of our decisions both at home and in the workplace. A basic decisionmaking tenet is that when we save people time, we create economic value. But when it comes to addressing congestion, the jury is still out on that matter, and it makes for some fascinating perspectives.
“Traffic congestion is up – and that’s a good thing.”

This is one of the conclusions in the press releases from the INRIX Annual Traffic Scorecard; it notes the relationship between traffic volumes and the national economy. Traffic volumes have dropped from their 2008 peak and it’s unclear how much of that is due to the recession as opposed to changes in other demographic trends (the increase in per-capita VMT couldn’t go on forever; at some point the laws of physics would intervene).

Exactly how much congestion is good congestion is a continuing point of debate. Some congestion is a sign of economic success, yet everyone is trying to solve it (and only Detroit appears to be succeeding). Being stuck in traffic is at least an annoyance and at most a real economic cost. This conundrum is well captured by Yogi Berra’s famous quote that “nobody goes there anymore; it’s too crowded.”

So how much congestion is okay? And how should we measure it?

The Texas Transportation Institute’s Annual Urban Mobility Report is, at 30 years old, the elder statesman of congestion monitoring reports; the 2012 edition identifies an annual $120B cost of congestion, related to the amount of time spent stuck in traffic. But that figure doesn’t sit well with a lot of folks for several reasons, but primarily due to the concern that the report promotes road building and sprawl. These concerns are detailed in critiques such as that from CEOs for Cities in 2010 and the Victoria Transport Policy Institute this year.

One critique of TTI is that the congestion value is measured against an overly optimistic baseline of free-flow conditions. Regardless of how much a traveler is frustrated by congestion, very few expect to experience no delay at all. The transportation planning industry was complicit in defining this process decades ago when Level of Service (LOS) grades were introduced; you only get an “A” on your report card if you eliminate congestion, whereas the most efficient use of physical space to move people and goods, regardless of mode, occurs between “D” and “F”. Most folks look at the adjacent photo of a congested multimodal corridor and see a failure in the transportation system. That might be true if those cars were truly stuck. But they’re actually crawling along at about 40 MPH, so while the train is indeed faster, we’re still probably making just about the most out of our highway investment. In fact, we might say “LOS E” should stand for “effective,” whereas many constituents feel it merely says “lose.” And the level of congestion associated with an individual bottleneck might not be so bad when averaged out over a longer trip, a concept explored by Montgomery County, Maryland in explaining the level of service concept to residents concerned about managing congestion near the Bethesda Naval Hospital and White Flint areas.

The digital revolution has created a robust data mining industry that facilitates our ability to both quantify and qualify performance. In baseball, the old chestnut of batting average is being supplanted by new and more subtle concepts like Wins Above Replacement. Similarly, in transportation planning, plain old travel time or travel delay statistics are being supplemented with concepts like Buffer Index and Planning Time Index that address travel time reliability and can be applied to improving predictability for all travel modes, particularly in appreciating the value of good system management and operations.

Seeking Quality Time

Another critique of the TTI annual rankings is that they only look at the time savings associated with auto travel and do not consider the quality or productivity of that time. Again, modal enthusiasts each have their arguments regarding preferences; transit riders enjoy the freedom to be engaged by a variety of work or pleasure activities that would distract a driver while motorists enjoy a greater control of their environment. But both the data and the discussion on the amount and value of total travel time and travel time reliability are important, particularly as government agencies and private sector interests (in both the land use and transportation arenas) consider the blend of access and mobility that make for sensible and sustainable investments.

The transportation planning industry has made enormous steps in defining “quality of service” for pedestrians, bicyclists, and transit users; it may be time to go back to the drawing board on qualitative values for auto travel as well to consider how measures like safety, comfort, and accessibility might better supplement or complement mobility. This is the challenge for each elected official, agency staff, consultant, and constituent: how to apply available data to make good decisions, separating the signal from the noise and the statistics from the spin.

The bad news is that there’s no ready answer as to how best to quantify and qualify congestion. The good news is that the information revolution is enhancing the ability for more detailed information and broader audience engagement in dialogue that can move the discussion forward.